Emerging satellite-based remote crop sensing, modeling, and novel analysis trends that involve machine learning and artificial intelligence offer unique opportunities to support a transition toward climate-smart sustainable agroecosystems. Nevertheless, our current scientific and technological knowledge seems insufficient to provide clear insights into farm management protocols that balance the goals of economic productivity and ecosystem sustainability. Key unknowns remain regarding how crops respond to biotic and abiotic stress both spatially and temporally, as well as how in-situ and remote sensors can monitor crop physiological responses to management practices and environmental stress at different scales. More specifically, there needs to be more understanding of how lessons from leaf-level studies using techniques such as gas exchange analysis and water potential measurements can be scaled and interpreted at the canopy and whole-field levels. Moreover, new insights combining leaf and canopy level spectroscopy and thermal information need to be linked to satellite-collected data observed at the satellite level.
The goal of this Research Topic is to feature research combining novel crop sensing approaches across spatial and temporal scales to monitor crop water use, abiotic and biotic stress, phenology, carbon, and other greenhouse gas fluxes. Additionally, we aim to highlight a combination of process-based and novel data analysis techniques to understand how crops respond to biotic and abiotic stressors and management practices across scales. Ultimately, these studies would identify crop response mechanisms based on well-understood biophysical and eco-physiological processes.
We invite research articles exploring plant eco-physiological responses, microclimate, canopy structure, phenology, stress, and other aspects relevant to advancing the understanding of crop-environmental interactions using leaf-to-satellite sensing platforms, novel scaling approaches, and data analysis techniques. We are interested in field and modeling studies providing ecological, biological, and physical insights using current or novel proximal or remote sensing approaches that would ultimately inform climate-smart farming practices. Contributions may focus on a range of temporal and spatial scales, linking processes from seconds to decades and from the leaf to the globe. We especially encourage studies on woody-perennial crops and/or multi-layer/species agroecosystems, considering the knowledge gap when comparing these systems to field annual crops.
Keywords:
plant physiology, stress, environmental interactions, phenology, canopy structure, microclimate, in-situ to satellite crop sensing, leaf and field interactions, Society Affiliation RT
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Emerging satellite-based remote crop sensing, modeling, and novel analysis trends that involve machine learning and artificial intelligence offer unique opportunities to support a transition toward climate-smart sustainable agroecosystems. Nevertheless, our current scientific and technological knowledge seems insufficient to provide clear insights into farm management protocols that balance the goals of economic productivity and ecosystem sustainability. Key unknowns remain regarding how crops respond to biotic and abiotic stress both spatially and temporally, as well as how in-situ and remote sensors can monitor crop physiological responses to management practices and environmental stress at different scales. More specifically, there needs to be more understanding of how lessons from leaf-level studies using techniques such as gas exchange analysis and water potential measurements can be scaled and interpreted at the canopy and whole-field levels. Moreover, new insights combining leaf and canopy level spectroscopy and thermal information need to be linked to satellite-collected data observed at the satellite level.
The goal of this Research Topic is to feature research combining novel crop sensing approaches across spatial and temporal scales to monitor crop water use, abiotic and biotic stress, phenology, carbon, and other greenhouse gas fluxes. Additionally, we aim to highlight a combination of process-based and novel data analysis techniques to understand how crops respond to biotic and abiotic stressors and management practices across scales. Ultimately, these studies would identify crop response mechanisms based on well-understood biophysical and eco-physiological processes.
We invite research articles exploring plant eco-physiological responses, microclimate, canopy structure, phenology, stress, and other aspects relevant to advancing the understanding of crop-environmental interactions using leaf-to-satellite sensing platforms, novel scaling approaches, and data analysis techniques. We are interested in field and modeling studies providing ecological, biological, and physical insights using current or novel proximal or remote sensing approaches that would ultimately inform climate-smart farming practices. Contributions may focus on a range of temporal and spatial scales, linking processes from seconds to decades and from the leaf to the globe. We especially encourage studies on woody-perennial crops and/or multi-layer/species agroecosystems, considering the knowledge gap when comparing these systems to field annual crops.
Keywords:
plant physiology, stress, environmental interactions, phenology, canopy structure, microclimate, in-situ to satellite crop sensing, leaf and field interactions, Society Affiliation RT
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.